Limited ; f​/m​/d - Enterprise Context Graph & AI

Research Fellow In The Global Content Group (Gcg) Engineering Team

At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong.

What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

As a Research Fellow in the Global Content Group (GCG) Engineering team, you will:

• Design and build an Enterprise Context Graph — a graph-based system that captures and persists agentic interactions and the memories derived from them, grounded in the structured enterprise knowledge on which those interactions are based
• Research and prototype approaches for continuous incremental learning, enabling the context graph to evolve and improve from captured interaction histories over time
• Apply ontology engineering methods to model interaction context, agent memory, and knowledge evolution in a semantically rich and queryable graph structure
• Combine data science techniques with ontology design to develop graph-based memory representations that support reasoning, retrieval, and learning
• Collaborate with a global team of software engineers, data scientists, and researchers on cutting-edge challenges at the intersection of agentic AI and knowledge representation
• Document and present your research findings, contributing to publications and internal knowledge-sharing

What you bring:

• PhD candidate (mid-to-late stage) or postdoctoral researcher in Computer Science, Data Science, Artificial Intelligence, Computational Linguistics, or a related field
• Deep expertise in ontology engineering and semantic web technologies (RDF, OWL, SPARQL) — you can design, formalize, and reason about complex graph-based knowledge models
• Strong data science background: proven experience with machine learning, embeddings, graph neural networks, or graph-based learning methods
• Solid programming skills in Python; experience with knowledge graph frameworks or ML libraries is a plus
• Research track record in agentic AI systems, memory architectures, continual/incremental learning, or related areas — ideally with publications
• Ability to drive independent research and translate findings into working prototypes
• Good communication skills in English (written and spoken);
  German is a plus

Where you belong:

We build the knowledge backbone of SAP — integrating business data into a unified context graph and delivering AI-powered experiences on top of it. Join a passionate team of engineers and researchers at the forefront of enterprise data management and applied AI.

Your set of application documents should contain a cover letter, a resume in table form, school leaving certificates, certificate of enrollment, current university transcript of records, copies of any academic degrees already earned, and if available, references from former employers (including internships). Please also describe your experience and skills in foreign languages and computer programs / programming languages.

This is a SAP global, strategic, paid, limited placement that provides candidates with opportunities to find purpose in their careers.